DEEP LEARNING VOICE ASSISTANT - Bakytkyzy А.; Smagulov Е.С.; Maden С.Б.; Zhexebay Д.М.; Kozhagulov Е.Т. (Bulletin of Abai KazNPU. Series of Physical and Mathematical sciences, 2022)
With the development of interface technologies in smart devices, voice assistants quickly gained popularity. These assistants are designed to use voice commands to provide a more convenient interaction with people. In this regard, one of the methods for implementing a voice assistant based on neural networks is proposed. Methods for implementing the main stages of creating a voice assistant have been studied. The article presents the results of testing a model based on a convolutional neural network. The following words were chosen as speech commands: yes, no, up, down, right, left, go, stop. This model classifies 8 speech commands with an accuracy of 86.63%. The neural network model best classified commands: yes, up, down, right, left, stop. The command to go is 66.67% accurate, and no is 76.4%, this is due to the similar sounding of the words down, go, no.